code: def simulate_do_nothing(self, observation):
      init_to_maintain_lines = np.where(
          (observation.time_next_maintenance > 0)
          & (observation.time_next_maintenance < 9)
      )[0]
      to_check_action = self.do_nothing_action
      to_maintain_lines = []
      for line_id in init_to_maintain_lines:
          if observation.line_status[line_id]:
              to_maintain_lines.append(line_id)
      # we do not disconnect the only line in advance
      if len(to_maintain_lines) == 1:
          rest_step = observation.time_next_maintenance[
              to_maintain_lines[0]
          ]
          if rest_step > 1:
              to_maintain_lines = []
      else:  # we only maintain the first line in `to_maintain_lines`
          to_maintain_lines = to_maintain_lines[:1]
  
      if (
          len(to_maintain_lines) != 0
          and self.step - self.last_disconnect_step > 3
      ):
          line_status = []
          for line_id in to_maintain_lines:
              line_status.append((line_id, -1))
          to_check_action = self.action_space(
              {"set_line_status": line_status}
          )
  
          (
              obs_simulate,
              reward_simulate,
              done_simulate,
              info_simulate,
          ) = observation.simulate(to_check_action)
          observation._obs_env._reset_to_orig_state()
      else:
          (
              obs_simulate,
              reward_simulate,
              done_simulate,
              info_simulate,
          ) = observation.simulate(to_check_action)
          observation._obs_env._reset_to_orig_state()
      return (
          obs_simulate,
          done_simulate,
          to_check_action,
          to_maintain_lines,
      )
  
file_path: PARL/benchmark/torch/NeurIPS2020-Learning-to-Run-a-Power-Network-Challenge/track2/rl_agent.py
imports: import os
  import numpy
  from copy import deepcopy
  from utils import process
  from powernet_model import PowerNetModel
  from grid2op.Agent import BaseAgent
  import torch
label_desc: Use image node_id 4 for calling the RLAgent obj's underlying member method code with example usage: obj.simulate_do_nothing(observation) and returns: obs_simulate,  done_simulate,  to_check_action,  to_maintain_lines